ABSTRACT. Solar radiation prediction is of great importance for many applications such as the PV power forecasting and the solar water heaters. The need of solar radiation prediction increase over time and certainly the accurate prediction can greatly improve the performance of these applications. In this paper the solar radiation is predicted for a winter day using ARMA model. The performance of this model to predict the solar radiation has been validated on a real database. Simulations results show that the effectiveness of ARMA model is proven to predict especially the small variation of solar radiation.

ABSTRACT. In this work, ultrastretchability is demonstrated in naturally rigid silicon solar cells using a corrugation technique. The corrugation is achieved by producing deep channels within the solar cell using the interdigitated back contacts technology. Stretchability is achieved by initially coating the back side of the photovoltaic cell using a bio-friendly elastomer. Moreover, the stretchability is shown to be dependent on the corrugated pattern which relieves the generated strain when applying a tensile stress. Finally, a stretching cycling test is performed on the solar cell to confirm its mechanical resilience.

ABSTRACT. Shortage of sub-transmission system capacities along with the need for reliable power supply have caused increased interest in distributed generation especially using solar photovoltaic source which is considered as clean energy. This paper investigated improvements in losses reduction using solar photovoltaic energy source. A test case sub-transmission network of Volta River Authority/Northern Electricity Distribution Company in the Northern Region of Ghana was used for the modelling and simulations. Power World Simulator Version 19 software was used to model the network. From the Power World simulator software simulations, data on voltage profile and active line losses were extracted and purposely used to train a neural network which output served as input to a fuzzy logic system. The neural network determined the most sensitive buses whilst fuzzy logic determined the optimal size of solar PV for placement in order to improve the voltage profile and reduce the line loses. Results indicated that, total active and reactive power losses reduced by 25.0% and 14.7% over the base case of no solar PV injection and optimal placement. The voltage profile of the entire length of the network saw an improvement to the value of 1 pu as a result of the solar PV integration using FL technique. Fuzzy logic is suitable for sub transmission line losses reduction.

ABSTRACT. In the last decade, solar photovoltaic energy generation has emerged as one of the leading vanguards of renewable energy source generation in South Africa. The considerable growth in the deployment of solar photovoltaic plants has grabbed the attention of worldwide project developers, investors and stakeholders. In the way indicated, more devised efforts are essential to wield the guarantee that solar photovoltaic plant equipment operate to meet the requirement of solar photovoltaic environment and facilitate the generation of energy as required. One such equipment susceptible to the harmonics and distortion generated by the connected inverters and resonances due to the non-linear loads is the step-up transformer. Harmonics and distortion are well known to introduce additional losses, hotspot temperature rise and reduction of the transformer service life. The rise in hotspot temperature yield abnormal levels of ignitable gases in the step-up transformer oil such that untimely failures may take place. The concentration of this gases suggests partial discharge and excessive heating. Recently reported studies evoke that the designing of solar photovoltaic plant transformers be more robust. This paper intends to contribute additional knowledge towards understanding the adverse effects related to harmonic currents in the step-up transformer for solar photovoltaic application. The winding eddy losses and structural part losses are examined under a harmonic profile to compute the service losses and resultant thermal requirements.

ABSTRACT. This paper presents general guidelines and description that would be adopted and used for the designing of a new photovoltaic (PV) system power plants. Reliable data sources required for a PV project are listed in this paper, as well as data to be adopted in Middle Eastern countries and more particularly in Lebanon. The information listed in this paper allows the reader to manage a quick feasibility study and check the payback periods and return on investment (ROI) before considering the launch of a certain project. Moreover, a listing of the latest available PV technologies will be shown by providing the key features of each. Once technologies are listed, one will be adopted for a particular project in the Middle East and its integration will be widely elaborated.

ABSTRACT. Over the last decade, South Africa has witnessed a generous amount in the number of failure rates in distribution solar photovoltaic (DSPV) energy transformers that has been derived from the knowledge deficit of the criterion for designing and an appropriate manner of specifying these transformers. Solar photovoltaic producers have underlined a considerable number of technical performance challenges that have not always been taken into consideration in the course of designing transformers. These challenges consists of harmonics and distortion, resulting in superheating of transformer metallic components, degradation of cellulose insulation, stray gassing of oil, short service life and a significant Total Ownership Cost (TOC) for solar photovoltaic producers. This paper present a case scenario of Dissolve Gas Analysis (DGA) carried out on a DSPV energy transformer following the anomalous stray gassing phenomenon unearthed after oil samples were taken for laboratory analysis during routine tests. The unit under study revealed anomalous gas concentrations of Hydrogen, Methane and Ethane, in which, are associate with corona, sparking and local overheating respectively. The findings highlight that a vague definition of the harmonic current loading in the course of designing transformers for DSPV application can potentially lead to the unit to be operated at a loading beyond specification.

ABSTRACT. The use of demand forecasting, benchmarking and response software is proposed as a solution for the Facilities Management division at Stellenbosch University to reduce the maximum demand cost component of campus facilities. This paper aims to address the demand forecasting segment by investigating three commonly used forecasting methods, namely Least squares estimation (LSE), Gaussian process regression, and Artificial neural networks. Forecast models implementing these methods are designed, trained on historical demand data and weather data from 2013 to 2015, and their response for 2016 is analyzed. The LSE forecast model yields the most accurate results for the following input parameters: forecasted temperature and UVA, time of the day, and the corresponding demand measurements of one and two weeks earlier.

ABSTRACT. Electrical Energy is one of the most common forms of energy in the world. Due to the increasing socio-economical style of living, the demand for electrical energy is increasing at an unprecedented rate, which transducers to high emission of greenhouse gases due to the combustion of fossil fuel. Two approaches can be applied to mitigate the emission, increased use of renewable sources of energy or retrofitting existing systems with technology. The latter was explored in this study. Predictive analysis was employed to predict the load demand of an individual and for a typical Mauritian household. The Fuzzy Time series and Probabilistic Neural Network were considered as predictive models and were modelled in KNIME Platform Analytics. It was found that the Probabilistic Neural Network was more appropriate for the load demand prediction yielding a Mean Absolute Percentage Error of 3.5 % as compared to the 4.7 % of the Fuzzy Time series.

ABSTRACT. An accurate heavy-duty truck (HDT) fuel consumption model is essential for estimating the truck energy consumption and evaluation of the effectiveness of energy saving strategies. Most of the existing models calculate the fuel consumption based on vehicle kinematics. However, based on recent truck field test data, we found the estimation discrepancies of several models published were considerable since they cannot accurately estimate the vehicle engine operation states and their base energy consumption rates. The engine power estimation is an essential part of the energy consumption model, which is the most likely cause of the model discrepancy. This inspired us to develop a generic modeling approach for vehicle engine-power estimation with a deep learning based on field experimental data. The data collected from a wide range of truck field tests were used for model development and fuel consumption model evaluation. The results show that the deep learning approach enables a much more accurate estimation of HDT engine power, and when applied as the input to the fuel consumption models (e.g., VT-CPFM, MOVES), average fuel estimation error is reduced to 13.71% from 28.9% which is the error resulted from the tractive power method. Besides, once calibrated with a small data set, it could be applied to various traffic scenarios without re-calibration. In addition, the Long Short-Term Memory (LSTM), a neural network structure component of the model, can accurately depict the fuel consumption during engine braking, which is largely missing in conventional HDT fuel models. The proposed model can benefit energy consumption related transportation planning and traffic operation studies that require more accurate vehicle fuel consumption estimation without detailed and complicated engine dynamics information.

ABSTRACT. Power converters (PCVs) such as inverters and rectifiers are crucial parts of wind energy systems (WES). Usually, the PCVs are subjected to high failure frequencies and consequence to the system downtime due to its structural complexity. Therefore, the main propose of this study is to develop an understanding prognostic approach dedicated to WES PCVs. The proposed method investigated the Insulated Gate Bipolar Transistor (IGBT) failure in PCVs. Therefore, it integrates the data-driven methodology. Usually, data-driven approaches based on a recorded database. Therefore, in this paper, we use the collector-emitter voltage as a precursor signal. In this work, the prediction of the Remaining Useful Life (RUL) of the IGBT device is achieved through the Feedforward Neural Network (FFNN) technique. Moreover, we used the time-domain analysis to extract useful information used as an input in the generation of the health indicator. In this work, the generation of the health indicator is achieved using the Principal Component Analysis (PCA) technique. The benefits of the proposed prognostic method are also illustrated with real IGBT accelerated aging database set under thermal overstress utilizing a DC at the gate.

ABSTRACT. Deep learning approaches have provided relevant contributions to electrical network fault detection and classification. Nevertheless, few works of literature exist on fault detection and classification using deep learning approaches. Fault detection using deep learning is a challenge due to the presence of legacy monitoring devices in the transmission lines, which do not allow the direct deployment of the model. Deep learning involves training of the system, thus sufficient amount of data is required. The challenge arises in acquiring appropriate data from low voltage network that could accurately be used to model the network. This study provides an analysis of fault detection and classification in the electrical secondary distribution network using the Recurrent Neural Network approach. The model was developed using the dataset obtained from the utility company in Tanzania (TANESCO), between the year 2012 and 2019. The data was obtained from the Automatic Meter Reading installed in a low voltage distribution transformer where the voltage, current, and power values were captured after every 20 minutes. The results revealed that the accuracy is more than 90%, which proves the suitability and relevance of deep learning for fault detection and classifications in the secondary distribution network. Deep learning approaches are still in the industry; hence remain the focus for the new researches to explore its usefulness in different applications.

ABSTRACT. Delivering high-quality electrical power requires an efficient, reliable protective system that can handle failures on transmission lines, which occur due to varies random causes. Detecting, classifying, and locating faults can prevent further damage to electrical supply equipment. The digital technology has brought unquestionable improvements in numerical relay design in terms of criteria signals estimation in a short time, better filtering, self-monitoring features, etc. However, it did not make a breakthrough in power system protection, as far as security, dependability, and speed of operation are concerned. The relaying task, however, can be approached as a pattern recognition problem. To enhance the performance of protection, the Artificial Neural Network (ANN) approach has been perceived by researchers in the field of power system protection. By monitoring the relaying inputs, the relay can be trained using ANN to classify the ongoing signals between faults and all other conditions. Therefore, this paper presents an intelligent method to design an online Simulink model of a distance relay. The Artificial Neural Network ANN, three-layer, Feed-forward networks with backpropagation algorithm for each of the three phases (voltage and current) were selected to achieve this design. The designed relay is composed of fault detection and fault type algorithm block, fault classification algorithm block, and fault location algorithm block, as well as the best network structure for each of the previous blocks, which have been determined. Moreover, the relay was evaluated under approximately all various fault types and different fault locations. The Simulation results show that the ANN method is effective in detecting faults on transmission lines.

ABSTRACT. Nowadays, “nearly Zero-Energy” Building (nZEB) is one of the most important facts in the whole of Europe. At first in this research, a design had selected for one office building using DesignBuilder software. This office building design will same for 20 other buildings for an official zone. The official zone site had selected in Sevilla, Andalusia, Spain. Afterward, a design had chosen for micro-grid which will be built in this official zone for not only fulfill the nZEB requirement by the European Union but also reduce the energy demand through the main grid. Moreover, design a Solar PV power plant on the rooftop of every office building to fulfill the required energy demand. Moreover, feasibility analysis (for Solar Irradiance) had done for 12 months of 2019 for Ronda Urbana, Norte, Sevilla Andalusia, Spain. Finally, one simulation had run without on-site power generation through renewable energy and another simulation had completed with on-site power generation. In on-site power generation had used large-size wind turbines to power generation through DesignBuilder simulation software which will fulfill almost 4 office buildings of the official zone. This work aims to create an nZEB official zone by using Solar PV generation and Wind Turbine generation system with microgrid by which the generation of Renewable Energy will be improved and make an economic impact for the development of a country.

ABSTRACT. Conventionally, the dc-dc converter needs a large input/output side electrolytic capacitor to suppress the voltage ripple which is caused by the PWM switching and achieve the desired voltage stable performance. For DC shipboard microgrids application, the large capacitors will increase the DC-bus short-circuit current dramatically when the short-circuit occurs. In this paper, a coupled-inductor-based filter, which ensures the lower voltage ripple and lower short-circuit current of the dc microgrid, is propose to realize the electrolytic capacitor. Moreover, the long lifetime film capacitor can be used to replace the electrolytic capacitor by reducing the required capacitance. The computer simulations and hardware experimental results are shown to verify the performance of the proposed coupled-inductor filter and short-circuit current reduction technique.

ABSTRACT. The operation of microgrids that contain microgeneration units such as wind, photovoltaic, and diesel power generations is always challenging towards the establishment of such microgrids. Such challenges arise due to the intermittent behavior of primary energy sources such as wind and solar. The largest island, Masirah, in the Sultanate of Oman, has significant potential of establishing microgrid using locally available sources of renewable energy. This paper presents the operation and control dynamics of a microgrid system that has significant potential to implement for Masirah Island. The case study microgrid system model has constructed using MATLAB/SIMULINK. The operational behavior of the case study microgrid is analyzed with and without a microgrid controller. It also presents the design and analysis of an efficient microgrid controller that is capable of maintaining an active power balance in the microgrid. The combination of a power absorber circuit and a power-frequency droop characteristic are incorporated in the proposed microgrid controller. The outcomes show that the designed controller is capable of maintaining microgrid frequency within the grid standard, which indicates the capability of operating such microgrid in isolated mode.

ABSTRACT. In recent years, the significant revolution of shipboard micro-grids (SMs) towards all-electric ships offered several advantages such as high efficiency, better maneuverability, and controllability. However, the application of power electronics onboard SMs, particularly for DC and hybrid ships leads to serious power quality issues. The application of passive power filters (PPFs) has been largely used to solve some of the power quality issues, such as harmonics contamination, power factor compensation, and voltage drop enhancement. However, analyzing some crucial factors such as the harmonic attenuation factor (HAF) and filters sensitivity factor (FSF) of these filters have not been attracted much attention. In this paper, a more in-depth mathematical analysis of the HAF and FSF of these filters is conducted with details. Moreover, some developed solutions to improve these factors are suggested. Based on intensive simulation studies of a practical hybrid ferry, which are carried out under MATLAB/Simulink environment, it has been demonstrated that the conducted analysis and proposed solutions can enhance the filtering performance of the PPFs.

ABSTRACT. This paper presents a performance evaluation of non-isolated bidirectional interleaved DC converter compare to conventional half bridge as an interface between DC bus and battery energy storage system (BESS) for energy storage application in a DC microgrid. Islanded DC microgrid is implemented using multiple energy storage elements in parallel to ensure redundancy, reliability, and modularity. The conventional Half Bridge  converter is compared with the interleaved topology (which is obtained by increasing the phase legs of half bridge) in terms of their frequency response analysis and SoC discharge when employed as interfacing converter between BESS and DC bus. The small signal or frequency response analysis is performed in Plecs using AC sweep, impulse response and multitone analysis. It is established in this study from the open loop bode diagrams of the converters that the corner frequency of the interleaved is almost two times the half bridge. This difference affected their SoC discharge when employed in a microgrid with the interleaved discharging at a rate almost twice that of half bridge. The interleaved also provides reduced current stress on the switch making it best suited for high power applications. The DC bus is 48V dc with a load power of 400W.

ABSTRACT. This paper presents the modelling of an off-grid micro-grid situated in a remote rural village in Eastern Cape province in South Africa. The modelling looks at the optimization studies for control dispatch strategies for the integration of wind power into the existing micro-grid which comprises an electric load supplied by photovoltaic power, battery bank for energy storage and a diesel generator. The optimization studies are performed using HOMER Pro® and aims to identify the best possible dispatch strategy for the dispatchable generation i.e. (diesel generator and battery storage) that minimizes load shedding and excess energy production in a system where the all the generation has been sized already. Four dispatch strategies built into HOMER Pro®, namely Cycle Charging, Load Following, Combined Dispatch and HOMER Predictive Strategy are tested. The aim of this paper is therefore to test and find which of the above dispatch strategies is the best fit for the rural village. Once the best-fit strategy has been determined, it is further customised and optimised for the rural village load profile.

ABSTRACT. Demand-Side Management Strategies (DSMS) modify the patterns of consumption of the customers. A proper design of a DSMS can reduce the curtailment of renewable energy sources while increasing their consumption. Additionally, the inclusion of DSMS in the planning of Stand-Alone Microgrids (SAMG) can reduce the total costs of the project. Despite the benefits that DSMS can bring to SAMG, there is a paucity of literature exploring the potential impacts of apply DSMS in the planning of SAMG. In this regard, the present work aims to evaluate the impact of using DSMS in the planning of SAMG over the sizing of Battery Energy Storage Systems (BESS). The work uses a Disciplined Convex based methodology to size the SAMG using historic data of load and weather variables. A study case shows that the proposed methodology reduces the installed BESS capacity in 17:76%, and the Levelized Cost of the Energy in 20:08% on average.

ABSTRACT. For temporary overloadings in power grids, battery storage systems can be an alternative to grid expansion. In the research project ”Hybrid-Optimal”, this concept was tested in a low voltage grid in Germany. A hybrid battery storage system was operated to prevent overvoltages in an area with significant decentral PV generation. In this paper, the algorithm and the software environment are presented and explained. Additionally, measurement data of a test period is analysed and evaluated. The battery system was able to fulfil its task in general during the test period. On several days, failures occurred, corrective measures are thus discussed in the paper.

ABSTRACT. Intermittency of renewable generation entails a large amount of flexibility and spinning reserve to enable secure and stable operation of the power system. The additional imposed cost due to accommodating renewables jeopardizes the economic value of renewable energy projects. Dispatchable renewable generation can help reducing the need for flexibility and spinning reserve. The optimal scheduling unit of an energy management system (EMS) for a dispatchable hybrid renewable power plant is described. It uses forecasting and optimization techniques to optimize the power output from a wind farm, a solar PV system and a battery energy storage system (BESS) such that dispatchable renewable generation is realized. Hence, the hybrid renewable power plant can participate in the interval-ahead electricity market in a similar fashion to conventional units and get dispatched. In addition to reducing the requirement for flexibility and reserve, a dispatchable hybrid renewable power plant can participate in the reserve market using part of the stored energy and any uncommitted power. This is a major leap towards an even higher penetration of renewables in power systems since it directly targets one of the main disadvantages of renewables. A case study is carried out to demonstrate the potential for integrating Sultanate of Oman’s Harweel wind farm with a solar PV system and a BESS to provide dispatchable hybrid renewable generation, with the aid of the introduced optimal scheduling unit of the EMS.

ABSTRACT. The growing supply from renewable energy systems (RES) into the distribution grid is leading to overloading of the existing grid lines. In that regard, battery storage systems (BSS) could be used to prevent power line overloading. If operated optimally, the BSS could buffer the high supply from RES and fulfill the (n 1) criterion replacing hence otherwise required grid expansion measures. In addition to the technical ability of the BSS, the cost efficiency of such an application must be verified. This paper proposes a new application strategy combining a grid-supporting and market-based operation of the BSS. The approach proposed determines, in a first step, the optimal dimensioning and operation plan of grid-supporting BSS in combination with a dynamic curtailment of RES to prevent grid congestion and ensure the (n-1) criterion. This approach has been applied to a real German 110 kV grid over a period of one year. In a further step, the BSS dimensioned were integrated into the EPEX spot market in order to generate revenues at times when no grid congestion is forecasted. The total costs of the grid-supporting use of BSS and dynamic power curtailment less the gains from the electricity market were then calculated and compared to the costs of the real planned grid expansions.

ABSTRACT. With increased efficiency and reduced initial investment, photovoltaic (PV) systems have become very popular. Installed capacities in every part of the globe are increasing dramatically annually, but will soon be capped due to grid integration limitations. This is mostly due to uncertainty in the generation capacity due to the unpredictable nature of renewable energy resources. This complicates integration with traditional generation dispatch schemes. The solution is the deployment of energy storage solutions. Storage technologies have exponentially improved over the years, but performance and price are still a limiting factor. Ultracapacitor manufacturing has matured, with capacitance values reaching thousands of Farads. They may be charged with high current resulting is high power and energy density. The purpose of this study is to quantify the improvement in the performance of a battery system with the addition of an ultracapacitor as an auxiliary energy storage device for solar PV applications. The improvement in performance is demonstrated through mathematical modelling and verified with simulation.

ABSTRACT. This paper presents a model for supporting the investment planning decision-making from the perspective of an independent energy provider that wants to integrate Battery Energy Storage Systems (BESS) in distribution networks. For supporting the decision, a conditional set of economically viable optimal solutions for the business model of buying and selling energy is identified in order to allow other decision criteria (e.g. loss reduction, reliability, ancillary services, etc.) to be evaluated to enhance the economic benefits as the result of the synergy between different applications of BESS. For this, a novel approach optimization model based on the metaheuristic Differential Evolutionary Particle Swarm Optimization (DEEPSO) and the Group Method Data Handling (GMDH) neural network is proposed for sizing, location, and BESS operation schedule. Experimental results indicate that after identifying the breakeven cost of the business model, a good conditional decision set can be obtained for assessing then other business alternatives.

ABSTRACT. The increasing connection of renewables and new loads is challenging the distribution grids. The Smart Transformer (a power electronics-based transformer with control and communication functionalities), can provide ancillary services to the distribution grids to support the grid management, in addition to the voltage adaptation.

The Smart Transformer is a natural connection point for hybrid (AC and DC) grids both at MV and LV levels and offer an optimal possibility to integrate storage and electric vehicles charging stations.

The keynote will define the concept of Smart Transformer presenting the topologies and controllers and highlighting how the ST can be modelled. New services enabled with the Smart Transformer technology, for instance load sensitivity evaluation in LV grids and voltage and frequency regulation in MV/HV grids, are explained, showing the laboratory validation through HIL and PHIL.

The technological challenges of the DC/DC converter with examples from porotypes built in the Power Electronics Laboratory at the University of Kiel are described.

Finally the design of the Smart Transformer as a grid-tailored Solid-State-Transformer will be presented.

ABSTRACT. The International Solar Alliance (ISA) is an alliance of 121 countries which lie either completely or partly between the Tropic of Cancer and the Tropic of Capricorn. Efforts are presently underway to get countries that do not fall within the Tropics to also join the alliance. Most of the countries that fall between the tropics are developing countries with agrarian economies and support over 40% of the world’s population. The primary objective of the alliance is to work for efficient exploitation of solar energy to reduce dependence on fossil fuels. The alliance aims at raising one trillion dollars needed to develop 1 Tera Watt (TW) of solar energy capacity by 2030 and contribute to the implementation of the Paris Climate Agreement. India is leading the path to a low carbon economy, and is among the top-five clean-energy producers globally and we are now eyeing production of 225 GW from renewables by 2022. Out of this, over 150 GW of renewable energy is installed or in the pipeline as of January 2020. The ISA can play a major role in harnessing solar energy for the growth and development of all partner countries.

ABSTRACT. In this paper, a Fuzzy Logic control (FLC) approach is proposed to track the maximum power in photovoltaic solar systems. In order to prove the performance of the proposed maximum power point tracking (MPPT) FLC algorithm, a comparative analysis is established with the conventional Perturb and Observe (P&O) control approach. The comparative study is carried out under variations in insolation and temperature. All obtained results prove the superiority of the FLC approach in terms of oscillation dynamics and response time of the system at starting and to track the maximum power point (MPP).

ABSTRACT. This paper considers comparison of dynamic performance of PI and fuzzy controllers for DC buck-boost and flyback converters. It is shown that fuzzy control is superior to classical PI control in terms of response time, stability and accuracy under different operating conditions. Moreover, it is underlined that fuzzy controller is more suitable to control buck-boost and flyback converters. Experimental results on dSPACE DS1104 board based test bench for the buck-boost in tracking mode, demonstrates its flexibility, robustness and efficiency.

ABSTRACT. Comprehensive evaluation is carried out to compare three different Cluttering Validity methods; Partition Coefficient, Partition Entropy and Proportional Exponent in the Evaluation of the results for Finding Electrical faults in industrial MV network using fuzzy clustering technique. Different data normalization methods and different range of alfa cut values for defuzzification are considered in the comparison process. The result shows that using Partition Entropy with Maximum Matrix normalization and 50% alpha cut gives the best effort saving of 95.15 in finding the fault.

ABSTRACT. With rising electricity costs, unstable electricity supply and an ever-increasing threat of global warming, it has become critical to save money and the planet. In an average household a geyser contributes to 30-50% of household electricity bill and the ‘always on’ control of the modern geyser still allow the geyser consume a considerable amount of power which puts strain on our already stretched Electricity Grid. The purpose of this paper is to provide a design of a project that will enable consumers to reduce and manage their Electrical Consumption by effectively controlling the use of their geyser through the use of timers and algorithms and also provide usage information based on their consumption. The Smart Geyser Controller fuse together hardware and software and use Internet of Things (IOT) for remote operation through the internet. The output of the project will be improved control for the user and reduced energy consumption.

ABSTRACT. The application of Internet-of-Things (IoT) technology in microgrid has converted them into intelligent and efficient systems and facilitated new applications such as smart metering. However, the introduction of these technologies have opened up new opportunities for security attacks that can destabilize the control operation of the power system. In this paper we consider a solar powered IoT-enabled DC microgrid and propose a new design that enhances the security of the communication using TLS 1.3 integrated version of MQTT (Secure-MQTT). We evaluate the design using a hardware based prototype. Results show the design provides communication encryption, integrity, and authentication with minimal impact to performance.

ABSTRACT. The smart grid is a new revolution in the energy sector in which information and communication system is integrated within the conventional electric power generation and distribution system. A key component of this system is the Advanced Metering Infrastructure, AMI, which enables twoway communication between consumer and utility company via a smart meter. In the smart home energy management system, SHEMS, the smart meter is responsible for Management System, SHEMS, is commissioned to monitor, control, trade, and log the energy consumption. Due to the diversification of the appliances in SHEMS and the deregulation of the communication protocol, the smart meter should be able to address the heterogeneity issues. In this paper, we propose an IoT smart meter architecture that addresses the heterogeneity problem in SHEMS. A prototype system using Raspberry Pi and Kaa IoT middleware is reported.

ABSTRACT. Reactive power compensation in grid connected ac-systems contributes to improve grid stability and reliability. Given that Active Front-End (AFE) rectifiers have the same power circuit topology of static VAR generators, they can ensure reactive power ancillary service besides their basic functions. In this context, this paper presents steady-state analysis and optimal DC-link voltage control for an AFE rectifier with reactive power ancillary service. Firstly, an investigation of the minimum required dc-link voltage level for optimal operation of the AFE rectifier with reactive power ancillary service has been performed. Then, an optimal design of the dc-link voltage controller has been developed in order to ensure the following control objectives: i) minimization of the transient dc-link voltage fluctuations in response to rough changes of the consumed active power ii) mitigation of the third harmonic component of the grid current under steady-state condition to comply with standards. A genetic algorithm-based on multi-objective optimization has been proposed to determine the gains of a PI based DC-link voltage controller. Simulation results demonstrated that the obtained control performances comply with the analytical results.

ABSTRACT. On the South African grid, Pump Storage Schemes (PSS) offer a range of benefits. They improve grid flexibility and service peak demand, while also increasing the base load utilization level for thermal plants. Financially they potentially offer higher returns compared to alternative peak generation options that use relatively high cost fuel. The Integrated Resource Plan for South Africa currently proposes adding gas turbines and batteries to the future grid for peaking capacity and increased flexibility, with no added PSS. This paper investigates the costs, services and contributions of pumped storage on the grid, the history of this technology and its potential future role. Within the South African context the paper aims to address the possible misconception of limited PSS site availability by providing an overview of site feasibility studies conducted in the last ten years, including estimated cost projections. Ultimately the paper argues that there is still potential for additional PSS on the future grid, and that further research should be done in order to analyse the energy modelling inputs and assumptions which are currently being used.

ABSTRACT. With regard to the ongoing changes in modern power systems towards increasingly decentralised systems, the coordination of generation assets and the corresponding dependency on Information and Communication Technology (ICT) becomes highly relevant. This work demonstrates the impact of varying ICT latency on the control and the behaviour of Distributed Energy Resources (DERs) in an exemplary medium voltage grid. Thereby, the focus is on the settling time, the overshooting and the stability of the active power flow control between the interface of the medium and high voltage grid. Furthermore, this work describes a general method to simplify and analyse the stability of distribution networks with high DERpenetration, especially their sensitivity towards communication latency between the network controller and the decentralised assets.

ABSTRACT. Increasing penetrations of small scale electricity generation and storage technologies are making an important contribution to the decentralisation and decarbonisation of power system control and operation. Although not currently realised, coordination of local distributed energy resources (DERs) and a greater degree of demand flexibility through digital aggregation, offer the potential to lower the cost of energy at source and to enable remuneration for consumer participation, addressing the rising costs of energy supply, which impacts strongly on all consumers. Methods are required to manage potential distribution network constraints caused by flexible DERs, as well as for determining the risk to delivery of flexibility from these DERs for aggregators. A heuristic network flexibility dispatch methodology is proposed, which can be used to calculate the probability of constraints, and any required adjustments of flexible agent positions to resolve them, at half hourly resolution. The aggregator can use this methodology to manage their portfolio risk, while a distribution system operator can estimate required flexibility to manage constraints down to low voltage level. Furthermore, a multi-market decision making tool is presented which optimises the participation of the aggregator portfolio in multiple national markets.

ABSTRACT. Due to the increasing profitability of photovoltaic systems, the penetration of decentralized domestic photovoltaic energy sources is growing. Contrarily to conventional energy sources, photovoltaic systems cannot be entirely controlled to meet the consumption. Their production can namely be cut-off, but cannot be increased. In a traditional grid, the production must follow the consumption at all times in order to keep frequency and voltage in a desirable range, but in a context of massive integration of renewable sources, it is preferable that consumption follows renewable production. This paper investigates how day-ahead consumption control strategies can reduce constraints on grid infrastructure, while increasing the penetration rate of decentralized photovoltaic. A method based on linear programming is applied to schedule day-ahead the operating schedules of household appliances in a residential microgrid. The obtained results illustrate how a smart microgrid can increase its profitability and provide energy management services such as peak-shaving or load-levelling.

ABSTRACT. Pursuing a common goal to mitigate climate change and contribute to a cleaner environment, end-users are taking over a more locally focused and sustainable lifestyle. In compliance to this social trend, recent years have brought a strong push towards electrification of transport and in Norway the interest in electricity driven personal cars has become particularly high. To realize the environmental benefit associated with electric vehicles, however, it is necessary to have enough power generation from renewable energy sources and sufficient capacity in the grid. Yet, renewable energy sources are typically intermittent in nature and pose challenges to the power system, while investments in increased grid capacity can be very costly. In this respect, the usage of energy flexibility to alleviate such challenges can be an efficient solution. This paper contributes to the research field by referring to eminent experiences from local market implementation trials in Norway – a country with a particularly high electric vehicle uptake rate. The paper pays specific focus to the flexibility opportunities stemming from charging of electric vehicles and to the “locality” as an important aspect of the market solution. Discussing key issues related to flexibility potential, local market design and implementation, the paper serves as a good reference point to support further steps towards local flexibility markets establishments.

ABSTRACT. The efficiency of solar cells depends mainly on the energy of the absorbed photons. This energy is directly related to the crystalline properties of the semiconductor materials used like absorber. So, this energy can be optimized using new solar cell structures based on thin film materials that absorb more photons. Therefore, using the graded CIGS like thin film materials with high reduced thickness, optimal gap makes it possible to the solar cell to absorb a wider photon of the solar spectrum. In the present work, exploiting SCAPS-1D simulator, we discuss, the effect of the P-CIGS band gap grading profiles on the electrical performances of thin film solar cell. The simulated solar cell is as 1.0µm-graded-CIGS/10nmN-CdS/150nmN-ZnO. We consider also, the effect of light spectrum and doping concentration variation of the absorber layer. An optimal efficiency of 22.92 % is recorded for 600nm light spectrum and linear grading.

ABSTRACT. Motorcycles form a popular mode of transport in East African countries, and policy in countries like Rwanda are encouraging a transition to electric motorcycles (EMs). This paper aims to identify the impacts of EM charging on a low voltage residential distribution network in future high uptake scenarios. A stochastic-probabilistic analysis is conducted on a residential network, looking at the effect of EM charging on voltage level, voltage unbalance as well as cable and transformer loading. The Monte Carlo Simulation method is used to account for the randomness in the placement of EMs along the network while the extended Herman Beta transform is used to account for the variability in the residential consumer loads. This paper found transformer overloading to be the limiting factor with regard to EM uptake for the sample network modelled. A sensitivity analysis then highlighted the effects that the feeder properties, transformer size as well as EM and residential load model had on the simulation outcome. The sensitivity analysis found the results most sensitive to the residential load modelling as this affected the transformer loading prior to any EM charging.

ABSTRACT. Proprietary software is used by utility companies throughout Europe to predict the district energy network parameters. Termis, NEPLAN and NetSim widely used in Denmark are limited to static or quasi-static models of electrical, thermal and hydraulic phenomena. Integration of new technology in a multi-energy network requires fully dynamic modeling to accurately estimate physical parameters and run model predictions. In the present study, dynamic modeling software for district multi-energy systems is presented and dynamic modelling framework Dymola is compared to the quasi-static software Termis. District heating system components are developed in Dymola, verified in Termis and applied to the case where the pump consumption is partially covered by the wind-generated power. The proposed modeling approach brings possibilities for (a) dynamic analysis of the integration of renewable technologies into the future district heating network and (b) comparison of existing and innovative multi-energy systems considering their real-time status and performance.

ABSTRACT. In this paper wind and solar energy based combined power generation system is modeled and connected to grid. For maintaining stable output level at the grid, DFIG wind turbine based energy conversion system is introduced and advance PWM technique is used in converters for reduction of harmonics and switching losses. A multistage inverter topology has been introduced in this paper. Purpose of this multistage inverter is to approximate the square wave output to a pure sine wave. For wind energy conversion Doubly Fed Induction Generator mechanism is observed in this paper. A Solar Energy Conversion System (SECS) has also been demonstrated. The site selected for the developed system is ‘Parkay Beach’ which is in Chittagong, Bangladesh. Solar and Wind energy data of this location is used for designing this system. The whole system is simulated using MATLAB/Simulink software.

ABSTRACT. The global warming and realisation that fossil fuel is limited, has been a drive over the years to move to renewable energy sources. Consequently, solar energy and other renewable energy sources are currently being exploited. The fast development of photovoltaic technologies makes the systems one of the leading methods to effectively exploit the RES. In recent times, the PV system are done at large to augment the classical energy supply. However, large-scale photovoltaic installations possess challenges of being susceptible to occurrence faults Therefore, it is imperative that faulty modules are detected and isolated to preserve the efficiency of the overall PV system. This paper presents a review of various faults often encountered in large-scale PV installation.

ABSTRACT. Growth of renewable energy (RE) micro-grids in Kenya has been encouraged by energy regulatory authority in pursuit for cheaper power generation and safety of the environment. However, such micro-grids experience operational challenges due the unpredictable weather patterns, requiring a continuous demand control scheme, which is detrimental to both customers and the micro-grid operator. This research models a renewable energy micro-grid with solar PV, wind turbine, hydro and a geothermal power plant for the base load. The transient stability study during times of adverse power imbalances shows that micro-grid is unstable during such time. Particle swarm optimization is developed to commit the units in an optimal scheme that considers load profile. This improves the control and operation of the micro-grid to minimize the frequency instability caused by power imbalance at times of severe shortage of generation from intermittent renewable sources.

ABSTRACT. The high penetration of power-electronics-driven power generation and the transition towards low-inertia power systems is affecting the fundamentals of grid operation. The loss of Synchronous Generators (SGs) together with their mechanical inertia and their frequency control mechanisms, brings new challenges to power system stability. Numerous decentralized control schemes for virtual inertia provision by emulation of SGs are presented in literature. However, the SG emulation has the drawback of nonlinear swing dynamics. As an alternative, the Linear Swing Dynamics (LSD) concept was proposed to exploit the smartness of power-electronic converters to not only secure the operation of future power systems but also enhance their dynamic behavior. In this work, we propose a feasible decentralized LSD control scheme for multi-machine power system with CPLs. The proposed control scheme is integrated into the state-of-the-art VSM controller and verified through simulations in MATLAB Simulink.

ABSTRACT. Inter-area low frequency electromechanical oscillation (LFEO) is one of the main threats to the stability and secure operation of interconnected power systems. Poorly damped growth of these oscillations can cause system instability and may even lead to blackouts. In such a context, Flexible Alternating Current Transmission System (FACTS) devices, particularly, Static Var Compensator (SVC), could be used to effectively damp inter-area LFEO by using a proper supplementary damping controllers. In this paper, a Fractional Order Proportional Integral Derivative controller (FOPID) based wide-area measurements is presented as an auxiliary control for the SVC in order to enhance power system stability and to improve inter-area low frequency oscillations. Different input signals are tested and the effectiveness of the novel controller compared to the integer order PID is demonstrated using a two-area four-machine test system. Generators rotor speed deviation is chosen as input signal for the proposed FOPID. The controller’s parameters are adjusted using Genetic Algorithm (GA) optimization. Simulation results conducted on a two-area power system show that the developed wide-area SVC-based FOPID controller is highly capable to damp inter-area low frequency oscillations.

ABSTRACT. Fundamental unit commitment approaches are of central importance in energy system modeling for the generation of detailed power plant schedules. However, existing approaches, which reduce complexity in a multi-stage process, often fail to generate realistic electricity prices. A new type of single-stage approach considers market-coupling implicitly so that, in addition to detailed power plant schedules, electricity prices reflecting real prices very well can be generated. In this paper, we show in a back-test for 2014 that an endogenously modeled market-coupling is the driving factor for the quality of resulting electricity prices. Conversely, it can be concluded that conventional multi-stage approaches show a significant distortion of modeled electricity prices due to missing price signals from neighboring market zones. Against the background of expanding trading capacities between market zones within the European power system, this issue becomes increasingly relevant when fundamentally modeling energy prices.

ABSTRACT. The protection of power distribution systems against lightning with high reliability is a critical aspect for power utilities. Lightning strokes influences the performance of a distribution systems. In this paper, we investigate the option of using streamer to minimize the effect of lightning in the Doulas MMS Coal 22kV plant. The network is modelled using MATLAB. Furthermore, we compared the surge arrestors and streamers and determined a suitable option for the application.

ABSTRACT. Due to its advantages Switched Reluctance Motor (SRM) may be used in low and middle power vehicles. However, since this motor is characterized by significant torque pulsation, insufficient power density and complex electric drive it is not widely used in nowadays. Thus, to improve their characteristics, in this paper it is analyzed SRM structures and proposed a proper relationship between stator and rotor poles with high energy efficiency. For the minimization of the torque pulsation a high frequency principle of magnetic flux formation with two section stator is proposed. For the adaptation of the proposed principle a resonant converter with soft switching, associated to two winding stator poles are used. In this way, the proposed modular SRM electric drive will be consisted by only four resonant converters. The SRM electric drive is simulated in MATLAB Simulink® and results are verified.

ABSTRACT. In this paper, we propose a socially-accepted local electricity pricing mechanism for households that is dependent on the electric load of a neighbourhood and is able to flatten out the neighbourhood profile. The used cost function is a piecewise linear approximation of a quadratic function.

The motivation for using this mechanism is that, with the energy transition at hand, unwanted high peak loads in electricity consumption as well as in renewable generation are expected in the distribution grids. To deal with these problems, electricity profiles need to flattened.

Following literature, quadratic cost functions have proven their ability to achieve such a system optimization, however, their problem is that customers find these pricing mechanisms too complex and would not be willing to participate when offered these prices. On the other hand, pricing mechanisms currently used in practice are often simple, and therefore socially well-accepted. However, these mechanisms are hardly giving any incentive to influence occurring peaks in the electricity profiles.

We show that the proposed mechanism is, according to the reactions of customers in a field test, and according to requirements presented in literature, a socially accepted mechanism. Furthermore, a numerical evaluation shows that our proposed mechanism can flatten out peaks on a neighbourhood level, albeit that its convergence is slightly slower than by using the quadratic cost function. These two aspects imply that the presented pricing mechanism has the potential to be useful in practice.

ABSTRACT. One of the problem facing the power industry is improper placement of the injection substations. This paper thus, presents an in-depth review of the various methods adopted in overcoming the menace. Intelligent based meta-heuristic optimization techniques has become a tool in solving numerous power system problems and has been critically considered. The aim of this research is to make available, relevant citations for learning progression on available editorials in the area of power distribution enhancement leading to further research interest.

ABSTRACT. Considering the effort and resources dedicated towards the Sustainable Development Goal number seven (SDG7) of "ensuring energy access for all", a post-2030 sub-Saharan Africa will be filled with a range of network solutions - main grids, minigrids and nano-grids. In time, some of the smaller networks will expand while others will be abandoned for better and resilient energy sources. However, such integration will pose technical challenges as most off-grid systems are designed and sized without any consideration of the main grid or other off-grid systems. This paper proposes that the identification of grid feed-in point into the minigrid network will be one of the critical decisions in integrating the main grid with once autonomous minigrids. Using power flow simulations of case study networks, results indicate that technical parameters such as losses and voltage drops on the local network vary significantly with choice of feed-in point, influencing the performance of the local network as well as its ability to accommodate more distributed energy resources in future. Based on these results, initial recommendations are made concerning the interconnection of such networks.

ABSTRACT. Cloud computing, mobility, and the Internet of Things (IoT) have created large data sets, which require more spectrum for data transmission. Unfortunately, the spectrum is a scarce resource, which is being underutilized by licensed users while the unlicensed spectrum is overcrowded. Cognitive radio technology has emerged as a promising solution to the underutilization of the spectrum. This study focuses on minimizing the signal overhead, improvement of QoS and the scalability of routing protocols to ensure the reliability of the network. Network simulator 2.31 equipped with a cognitive radio network patch is used to simulate the proposed scheme in Linux operating systems. The study uses a meta-heuristic algorithm called cuckoo search algorithm inspired by nature to establish a stable path with enough resources. From the literature review, researchers identified techniques, which can achieve good performance in routing in terms of delay, dropped packets and QoS in ad hoc networks. The simulations depict that the proposed scheme performs better than the existing scheme.

ABSTRACT. Sub-Saharan Africa requires affordable, reliable, and sustainable electricity to boost its economic, social, and human development. The main challenge posed to the region's electricity sector is the large investment gap needed to finance new power projects. The employment of new and innovative financing options is required to bridge this investment gap. Independent power projects have become one of the fastest-growing sources of new finance in the region. However, their development is constrained by the limited availability of debt finance for project implementation. The limited capital and bureaucratic burden of traditional financial institutions coupled with the high risks in the region ensures that the debt finance required by independent power projects is raised only after an arduous voyage and at high interest rates. We address these challenges by proposing a novel decentralized finance instrument, a blockchain special purpose vehicle that streamlines the processes in the financial layer of a traditional special purpose vehicle - finance mobilization, revenue collection, and revenue disbursal. Specifically, the proposed decentralized finance instrument facilitates the mobilization of finance for the special purpose vehicle from a location-independent crowd, revenue collection from the electricity offtaker in a risk-mitigated manner, and disbursal of eventual project revenues to investors.

ABSTRACT. The growing presence of Distributed Generation has kept alive the discussions for the active integration of medium/low-voltage power consumers into the energy market. Besides technical and economic difficulties faced so far, another point of view emerges from use blockchain technologies to make the Transactive Energy approach a reality. The current article presents a distributed application model for energy management and trade between members of a shareable consumption group, a kind of Distributed Generation regulated by the Brazilian Government. It also showcases the methodology of the crypto-currency Sharing Electricity in Brazil that can be used to allow power exchange operations at the scope of micro/mini-grids.

ABSTRACT. Contract-for-Difference financial instruments are available to renewable electricity generators in day-ahead electricity markets to allow them to hedge against price and volume risk, together known as {\em revenue risk}. Traditional CfDs while designed to hedge revenue risk, introduce other new risks such as counterparty credit, margining and third-party risks. We therefore propose a novel financial instrument -- an Ethereum blockchain-based dual escrow smart contract, to serve as the mediator in a CfD agreement between a renewable electricity generator and supplier. This financial instrument addresses hedging related risks that result from traditional CfD agreements in day-ahead electricity markets. In this paper, we design the logic of the financial instrument, translate this logic to smart contract codes and demonstrate its expected performance. Overall, the proposed financial instrument has the benefits of reducing hedging related risks inherent in traditional CfDs. Likewise, it enables secure, efficient, cost-effective, consistent, reliable, transparent and frictionless transactions between contracting parties in a CfD agreement.

ABSTRACT. This paper proposes a novel tariff regime for peer-to-peer energy trading, with an aim to increase transmission efficiency and grid stability by penalising long distance power transactions. In this scheme a portion of the transacted energy is withheld based on the electrical distance between buying and selling parties, calculated here according to the Klein Resistance Distance. This tariff regime is simulated using a dataset of producers and consumers over a 24-hour period. First, a notional marketplace equilibrium simulation is performed, in which consumers can optimally activate demand response resources to exploit local availability of energy. Consumers are observed to move some demand away from peak times to make use of local generation availability. These simulated market out-turns are then used as inputs to a time series power flow analysis, in order to evaluate the network's electrical performance. The regime is found to decrease grid losses and the magnitude of global voltage angle separation. However, the metric whereby taxes are calculated is found to be too skewed in the utility's favour and may discourage adoption of the peer-to-peer system. The method also attempts to encourage regulatory adoption by existing grid operators and utilities. Some counter-intuitive allocations of tokenised energy occur, owing to specific consumers' demand profiles and proximity to generators.

ABSTRACT. This paper proposes and discusses the idea of using nascent blockchain hosted prediction markets as a decentralised crowd sourcing method for renewable energy forecasting. This method is further used as a risk management and hedging tool against volatility in weather variables they depend on. While existing approaches have been centralised by nature, with limited sources of input data and models, prediction markets allow anyone to participate in forecasting by betting on an outcome and earning profits for correct results. Since they have mercenary motivations, these participants are most likely to provide reliable and accurate information. Moreover, renewable energy producers can participate in these prediction markets to hedge against low income periods of time due to poor weather conditions. This paper delivers a conceptual framework to exploit prediction markets in a blockchain platform with the aim of forecasting and hedging of renewable energy sources. The potential financial gain from applying this approach has been demonstrated through a case study for a typical small wind power producer.

ABSTRACT. The purpose of this work is to design a covert agent structure that can create a non-zero frequency deviation in the load frequency control (LFC) system and illustrate the necessity of a secure communication network for the load frequency control. LFC systems are one of the most time-consuming control loops of power systems that are vulnerable to cyber-attacks and disturbances. Cyber-attacks like covert attacks can affect the frequency performance of the LFC system without being detected, as the covert adversaries cancel out the influence of the deceptively added actuation signal by deducting the corresponding effect from the measurement signal. In this paper, a covert agent with feedback structure is formulated and it is shown that the covert adversary can take control of LFC system through the covert reference signal and can keep the relative offset between actual frequency deviation of LFC system and the measurement signal received by the integral controller within safe limits, such that the attacker remains undetected.

ABSTRACT. The fundamental changes in power supply and increasing decentralization require more active grid operation and an increased integration of ICT at all power system actors. This trend raises complexity and increasingly leads to interactions between primary grid operation and ICT as well as different power system actors. For example, virtual power plants control various assets in the distribution grid via ICT to jointly market existing flexibilities. Failures of ICT or targeted attacks can thus have serious effects on security of supply and system stability. This paper presents a holistic approach to providing methods specifically for actors in the power system for prevention, detection, and reaction to ICT attacks and failures. The focus of our measures are solutions for ICT monitoring, systems for the detection of ICT attacks and intrusions in the process network, and the provision of actionable guidelines as well as a practice environment for the response to potential ICT security incidents.

ABSTRACT. With the increasing interdependence of critical infrastructures, the probability of a specific infrastructure to experience a complex cyber-physical attack is increasing. Thus it is important to analyze the risk of an attack and the dynamics of its propagation in order to design and deploy appropriate countermeasures. The attack trees, commonly adopted to this aim,have inherent shortcomings in representing interdependent, concurrent and sequential attacks. To overcome this, the work presented here proposes a stochastic methodology using Petri nets and Continuous Time Markov Chain (CTMC) to analyze the attacks, considering the individual attack occurrence probabilities and their stochastic propagation times. A procedure to convert a basic attack tree into an equivalent CTMC is presented. The proposed method is applied in a case study to calculate the different attack propagation characteristics. The characteristics are namely, the probability of reaching the root node $\&$ sub attack node, the mean time to reach the root node and the mean time spent in the sub attack nodes before reaching the root node.Additionally, the method quantifies the effectiveness of specific defenses in reducing the attack risk considering the efficiency of individual defenses

ABSTRACT. On-line sharing of cyber-security information is necessary to effectively counter cyber-attacks. An online cyber-security analytics system for detecting and mitigating cyber-attacks and sharing information between Critical Infrastructure operators and regional and national authorities and also internationally is presented. The system contains one part which acts as a Security Operations Centre at Critical Infrastructure-level, with the capability to automatically mitigate attacks, and a part on meta- Critical Infrastructure level which, on a pan-European scale, gathers and analyses cyber-security information provided by the Critical Infrastructure operators and provides the results of the wide-area cyber-security analytics to authorities and back to the Critical Infrastructure operators. A use case of the system detecting and mitigating an attack is presented.

ABSTRACT. In this paper, the 2RC electrical equivalent circuit of the Li-ion battery is considered for deducing the state space model. The estimation of state of charge (SoC) and terminal voltage of the battery is derived through Coulomb counting and Extended Kalman filter for constant current discharge as well as for Urban Dynamometer Driving Schedule (UDDS) cycle. The parameters required for the state space model are determined experimentally for different discharge currents of a single cell. The design of battery pack for different power requirements like two, three and four-wheeler electric vehicles (EVs) from these 18650 cells is deduced and the performance indices are estimated based on an UDDS cycle. The estimated SoC and terminal voltage are compared with those obtained through preliminary Coulomb counting and 2RC model.

ABSTRACT. This abstract presents a complete design of a Heating Ventilation Air Conditioning (HVAC) system for battery rooms using modern components and techniques to achieve a cost effective design that will perform the required function without compromising the quality of the system. This abstract focuses on all the active systems which involve electrical design approach, installation and layout. This paper presents all the technical information related to an efficient design proving the benefits and necessity of the design.

ABSTRACT. Uncertainty in electricity demands are balanced in real-time using fast reacting flexible generators such as hydro and gas turbines. The generation needs to act as a fast ramping reserve for frequency control. According to the South African Integrated Resource Plan more flexible generation will be required to integrate the increased variable renewable energy generation and this will be provided by gas turbines. More studies need to be done to verify whether renewables, gas and diesel combination will provide the energy security South Africa currently obtains from base load stations. As supplementary reactive power and additional inertia may be needed to ensure voltage stability with the addition of high proportions of non-synchronous PV and wind generators. Pumped Storage can alleviate this issue as it is another form of flexible generation with fast ramping capacity, stored energy, and system inertia to provide security and stability to the grid. This paper investigates the services and contributions of pumped storage on the grid and develops levelized cost of energy curves for pumped storage, gas turbines and batteries. The paper further highlights the issues with modelling pumped storage in long term planning models and makes recommendations

ABSTRACT. The increasing installations of renewable hybrid energy systems in commercial buildings require system sizing to ensure that the designed hybrid system will meet the load demand of a targeted commercial building with minimum life cycle cost. In the commercial sector, photovoltaic renewable is preferred because both its generation and consumption take place during the day. Optimal sizing techniques are required for designing reliable and economical hybrid energy systems. This paper presents optimal sizing of grid-connected hybrid photovoltaic-battery-diesel energy system that meets the load demand of a targeted commercial building with minimum life cycle cost using HOMER software. For the proposed hybrid system, results indicate that 18 kW photovoltaic-6 batteries-15 kW inverter provides the economic system while load following dispatch strategy gives a life cycle cost of $85195 that is lower than $86847 using cycle charging alternative.

ABSTRACT. In this paper, a model to optimize the operation of a hybrid energy system connected to a healthcare institution is developed. The proposed hybrid system consists of a dual axis PV tracking system and electrical energy storage device supplying power to a critical load in conjunction with an existing grid connection. The healthcare entity is subjected to time-based pricing and maximum demand charges. The case study falls within the city of Bloemfontein in South Africa, where solar irradiance is in abundance. The developed model and presented algorithm aim to optimize the power flows between the hybrid energy systems and energy storage scheme in order to minimize the grid energy usage and associated costs based on the Time-of-Use tariff while simultaneously reducing the maximum demand charges from the utility. The simulation results have revealed that the developed optimal control model was able to manage the power flows of the proposed system connected to the healthcare entity. Employing the proposed optimal control strategy may potentially reduce the entity’s monthly operation cost by approximately 60%, while maximizing the local renewable energy productions and use of the energy storage scheme.

ABSTRACT. A real-time simulation study, where a control system replica is connected to a real-time electromagnetic transient simulator in closed-loop (known as hardware-in-the-loop), is an essential tool in commissioning or refurbishment projects of major power system devices such as SVCs, HVDCs and other FACTS devices: it allows to reduce commissioning risks and it is useful throughout the life of the system. It is however an expensive endeavor in time, manpower and equipment. The present paper aims at presenting a more affordable and efficient way to pursue real-time hardware-in-the-loop commissioning studies by using low-cost commercially off-the-shelf computers and hybrid simulation (electromagnetic transient and transient stability modeling) to increase the scale of the power system that can be simulated in real-time without increasing the required real-time hardware resources. To illustrate this approach, a hardware-in-the-loop experimental setup is presented and detailed: based around the control system replica of Hydro-Québec’s Figuery SVC, this setup relies on a low-cost 4-core personal computer.

ABSTRACT. Use of Energy Sources have both positive and negative environmental effects. Sustainability in the development of energy sources requires methods and tools to measure the environmental impacts of such deployment and this includes Renewable Energy Sources. This paper considers the environmental impacts of Solar PV in an existing Diesel-PV minigrid using Life Cycle Assessment (LCA). Modified ReCiPe Model is adapted for the analysis ecosystem and health effects. The emissions are determined using HOMER software. Simulated results reveal that hybrid Diesel (D)-Solar (PV) is preferred in reducing the environmental effects at an increased emission allowable cost.

ABSTRACT. Flashover due to pollution of overhead transmission line insulators (OHTL) is a major source of faults in the electric power transmission system. Insulators are exposed to the outdoor environment and become polluted by different types of pollutants that end up causing faults, like flashover in the transmission of electric power. In this paper, the investigation of the potential distribution efficiency of polluted 132kV AC transmission line insulators was conducted. MATLAB was used to model and simulate the polluted insulators and comparison was made between not polluted and polluted insulators. Due to pollution of the OHTL, the potential distribution on a string of suspension insulators became non uniform leading to a decrease in efficiency. The results show that the value of a capacitance K ratio increases from 0.2 to 1.0 which led to an efficiency decrease from 99.9% to 31.07%.

ABSTRACT. This paper presents a scheme for allocating active power loss in the context of smart grid to load nodes. A technique that uses load-edge set and edge-load set is used to determine load nodes that use a specific segment of transmission network. Losses are subsequently allocated based on the proportion of active power demand at load nodes. A model of IEEE \(39\) bus test system in PYPOWER \(5.12\) was used to test the scheme. The result obtained shows that, the scheme can be used as means of allocating transmission network losses to load nodes in electric power networks.

ABSTRACT. Rapid rate of development in modern times, proliferation of more sophisticated electrical appliances and expansion of industries calls for increases in electric power generation and upgrading of sub-transmission networks. This paper investigated the power system of the Yendi – Bimbilla – Kete Krachi sub–transmission line with regard to voltage stability and power losses. To achieve this, the sub–transmission line was modelled and simulated using NEPLAN V543 software. Base case simulation results indicate a drop in voltage below the Public Utility Regulatory Commission (PURC) acceptable limits giving rise to the use of Flexible Alternating Current Transmission System technology. This came in handy to improve power system performance of the sub-transmission line without altering its size or the number of circuits. Deploying Static VAr Compensator (SVC) and Thyristor Controlled Series Capacitor (TCSC) onto the network, power system constraints of voltage instability and higher power losses reduced appreciably. Out of six scenarios considered, installation of 2.6 MVAr SVC at Bimbilla gave an average voltage improvement of 6.34%, 21.97% reduction in active power losses, and 66.64% improvement in the reduction of reactive power losses over the respective values of base case. By way of recommendation, 2.6 MVAr of SVC should be incorporated at Bimbilla for effective voltage profile enhancement and losses reduction.

ABSTRACT. The aging of insulation materials is of great importance in determining useful lifetime of electrical equipment. Mechanical and electrical tests were conducted on aged 6 kV porcelain support insulators, which were in service for 70 years in an indoor substation. The mechanical tests included compression, tension and bending of the insulator until failure. The electrical tests included application of standard lightning impulse voltages and determining the 50% probability flashover voltage for both positive and negative polarities and determining 50 Hz AC flashover voltage. In electrical tests, puncture did not occur. Across all of the tests, the insulator was found to conform to the initial parameters specified by the manufacturer. It was found that the deterioration of the porcelain insulator had not reached an excessively high level despite the substantially long service time.